投稿時間:2022-09-12 01:19:37 RSSフィード2022-09-12 01:00 分まとめ(20件)

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IT	気になる、記になる…	Appleの10月の発表イベントでは新型iPad Proと新型iPadに加え、2つの新型Macが登場か	https://taisy0.com/2022/09/12/161837.html	apple	2022-09-11 15:48:21
IT	気になる、記になる…	Apple、早ければ年内にも｢iPhone｣を定額制で販売するサービスを導入か	https://taisy0.com/2022/09/12/161834.html	apple	2022-09-11 15:17:46
python	Pythonタグが付けられた新着投稿 - Qiita	素数p=x+y (x,yともに1以上)とすると gcd(x,y)=1 らしい	https://qiita.com/ikiuo/items/95ffae7ae6467b6ebfc6	widthbitmapintgcdx	2022-09-12 00:16:02
Ruby	Rubyタグが付けられた新着投稿 - Qiita	正規表現 備忘録	https://qiita.com/mshkki/items/13a6e2ee51bc1fad099c	正規表現	2022-09-12 00:11:08
AWS	AWSタグが付けられた新着投稿 - Qiita	【AWS】AmazonConnectのコンタクトフロー内でLexを呼び出す	https://qiita.com/Aichi_Lover/items/748a0f469378235d258f	amazon	2022-09-12 00:25:33
Azure	Azureタグが付けられた新着投稿 - Qiita	ReactアプリをStatic Web AppsとCosmos DBにデプロイ(ドメイン登録まで)	https://qiita.com/takatoshiinaoka/items/fd7c0a4a53b4badd7c4f	azure	2022-09-12 00:23:34
海外TECH	DEV Community	Docker Log Rotation Configuration Guide | SigNoz	https://dev.to/danielfavour/docker-log-rotation-configuration-guide-signoz-3jc3	Docker Log Rotation Configuration Guide SigNozThis article was originally posted on SigNoz and written by me It is essential to configure log rotation for Docker containers Log rotation is not performed by default and if it s not configured logs on the Docker host can build up and eat up disk space This guide will teach us how to set up Docker log rotation Logs are an essential piece of telemetry data Logs can be used to debug performance issues in applications They produce a thorough list of the events that take place in your application which can be used to troubleshoot issues and identify the root cause of a problem With containerization it is easier to scale applications But the operation complexity has increased manifolds Containers are ephemeral Frequently changing container based environments are challenging to monitor Docker logs can help debug performance issues Applications in Docker containers emit logs through stdout and stderr output streams The logging driver that you choose can access these streams Based on your logging driver you can configure the format and storage of Docker logs You can also send the emitted logs to a central log management system Before deep diving into configuring Docker log rotation let s briefly overview Docker logs A brief on Docker LogsLogging in Docker is different from applications hosted on physical or virtual hosts Container environment is dynamic and troubleshooting is more complex In Docker primarily there are two types of log files Docker daemon logsThese logs are generated by the Docker daemon and located on the host It provides insights into the state of the Docker platform Docker container logsDocker container logs cover all the logs related to a particular application running in a container Docker does not impose a size restriction on logging files Hence they will inevitably increase over time and consume storage if left unchecked You can imagine the growth of log files over time and the amount of storage they would require in a scenario where you have numerous containers running Limiting the size and quantity of locally stored log files is the main goal of log rotation Docker logs must be cycled at predetermined intervals because manually deleting logs is a laborious task But the first question is where are Docker logs stored Where are Docker logs stored Logs are often kept on the Docker host because containers are stateless failing to remember or save data from previous actions Docker uses the JSON file logging driver by default and it records all stdout and stderr output in JSON format Log files are created for each container and are generally stored at var lib docker containers container id container id JSON logDocker provides support for multiple logging drivers You can check out other logging drivers available To know your current logging driver for Docker Daemon run the following command docker info format LoggingDriver Configuring Docker Log RotationLet s first configure the Docker daemon to a particular log driver To configure the Docker Daemon to a particular log driver Step Go to the Docker daemon configuration file location On Linux etc docker directoryOn Windows C ProgramData docker config daemon jsonStep If your logging driver hasn t been set yet use the following command to set it up log driver local or log driver json file You can specify any log driver of your choice but Docker recommends using the local logging driver to prevent disk exhaustion because it performs log rotation by default Step Add configuration for log rotationAdd the following code to the daemon json file after editing or creating it to rotate the log The final file when using json file driver looks like this log driver json file log opts max size m max file You can also update the parameters for local logging driver using the same format log driver local log opts max size m max file Step Save the file and restart docker systemctl restart dockerThe change in the default logging driver impacts only the containers created after modifying the daemon configuration The existing containers carry the initial configuration of the logging driver In order to update their logging driver for existing containers they must be recreated with the preferred options Configuring Log Drivers and Rotation for specific containersTo configure a container to use a different logging driver than the Docker daemon s default use the log driver flag You need to include the container ID or container name alongside the command docker run it log driver json file nginxThe log driver flag specifies the log driver you are assigning to that container In the above example the log driver assigned to the container is the json file To find the current logging driver for a running container if the daemon is using the json file logging driver run the following command docker inspect f HostConfig LogConfig Type lt CONTAINER gt Then to setup log rotation for the specified container run the below commands docker run log driver json file log opt max size m log opt max file nginx echo hello worldAnother way to do this is by running the below commanddocker run log opt max size m log opt max file nginx latestSimplifying the above command docker run log opt max size mIt tells Docker to limit the size of your Docker log file log opt max file It instructs Docker to store no more than log files When the limit is met Docker is instructed to destroy the older files nginx latestThe container image nameYou can also have a look at the logging options the JSON file accepts Final ThoughtsIn this guide we learned how to set up Docker log rotation Container environments are highly dynamic with multiple layers of abstraction As a result it s hard to debug such environments and logs can play a critical role in providing much needed visibility into performance issues Docker provides various terminal commands to interact with Docker logs You can use your console to view logs while developing your application or debugging a specific scenario But in production environments it s advisable to centralize your logs for storage and analysis That s where a log management solution comes into the picture The first step for efficient log management is log aggregation Once the logs are aggregated you need to store them and set them up for analysis There are multiple log management solutions out there But which solution is best suited for modern distributed cloud native applications SigNoz a full stack open source APM can help you to store manage and analyze logs at scale It correlates all your telemetry data logs metrics and traces into a single suite of monitoring Apart from logs SigNoz can also help you monitor metrics and track the performance of user requests across services using distributed tracing Log management in SigNoz Currently under development SigNoz is built to support OpenTelemetry natively OpenTelemetry an open source project backed by Cloud Native Computing Foundation can be used to aggregate and process logs from multiple sources OpenTelemetry is quietly becoming the world standard for instrumenting cloud native applications to generate telemetry data It s easy to get started with SigNoz It can be installed on macOS or Linux computers in just three steps by using a simple installation script The install script automatically installs Docker Engine on Linux However you must manually install Docker Engine on macOS before running the install script git clone b main cd signoz deploy install shYou can visit our documentation for instructions on how to install SigNoz using Docker Swarm and Helm Charts You can check out SigNoz GitHub repo here Further ReadingSigNoz an open source alternative to DataDog	2022-09-11 15:36:16
海外TECH	DEV Community	What is machine learning?	https://dev.to/makendrang/what-is-machine-learning-1mkl	What is machine learning Machine learning is an important part of the growing field of data science Using statistical methods algorithms are trained to classify or predict revealing key ideas for data mining projects This information then guides decisions in your app and business ideally influencing key growth metrics As big data continues to grow and grow so will the market demand for data scientists They are asked to help identify the most relevant business questions and data to answer Machine learning algorithms are typically built using frameworks such as TensorFlow and PyTorch that accelerate solution development How does machine learning work The University of California Berkeley divides its learning system of machine learning algorithms into three main parts Decision MakingGenerally machine learning algorithms are used to make predictions or classifications Based on tagged or unnamed input data the algorithms generate model estimates in the data Error functionThe error function evaluates model predictions Given a well known example the error function can perform comparisons to evaluate the accuracy of the model Model Optimization ProcessAs the model fits better to the data points in the training set weights are adjusted to reduce the discrepancy between known examples and model estimates The algorithm repeats this evaluation and optimization process updating the weights individually until the accuracy limit is reached Machine learning methodMachine learning models fall into three basic categories Supervised machine learningSupervised learning also known as supervised machine learning is defined using labeled datasets to train algorithms to accurately classify data or predict outcomes As input data is entered into the model the model adjusts the weights until it fits properly This is done as part of the cross validation process to ensure that the model avoids overfitting or undertreatment Supervised learning helps organizations solve a variety of real world problems on a large scale such as sorting spam to a separate folder from the inbox Techniques used in supervised learning include neural networks naive cells linear regression logistic regression and random forests Unsupervised machine learningUnsupervised learning also known as unsupervised machine learning uses machine learning algorithms to analyze and aggregate unlabeled datasets These algorithms detect hidden patterns and data sets without human intervention This method is ideal for exploratory data analysis cross selling strategies customer segmentation and image and pattern recognition as it can detect similarities and differences in information It is also used to reduce the number of features in the model through the dimensionality reduction process Principal Component Analysis and Single Value Analysis are two popular approaches for this purpose Other algorithms used in unsupervised learning include neural networks k mean clustering and probabilistic clustering techniques Semi supervised learningSemi supervised learning offers a good middle ground between supervised and unsupervised learning During training we use a small labeled dataset to guide classification and extract functionality from a large unlabeled dataset Semi supervised learning can solve the problem of lack of sufficiently labeled data for supervised learning algorithms It is also useful when classifying enough data is too expensive Reinforcement machine learningAdvanced machine learning is a machine learning model similar to supervised learning but the algorithm is not trained on data samples This model learns by trial and error Successful outcome chains are enriched to develop optimal recommendations or policies for specific problems Popular machine learning algorithmsMany machine learning algorithms are commonly used Among which Neural networksNeural networks mimic the functioning of the human brain and have many associated processing nodes Neural networks excel in pattern recognition and play an important role in applications such as natural language translation image recognition speech recognition and image creation Linear RegressionThis algorithm is used to predict scalar values based on linear relationships between different values For example this technique can be used to predict house prices based on a region s historical data Logistic RegressionThis guided learning algorithm expects categorical response variables such as yes no answers to questions It can be used for applications such as spam classification and online quality control ClusteringUsing unsupervised learning cluster algorithms identify patterns in the data so they can be aggregated Computers can help data scientists by identifying the differences in data that people have overlooked Decision treesDecision trees can be used to predict numerical values and rank data A decision tree uses a branched series of related decisions that can be represented in a tree diagram An advantage of decision trees is that they are easier to validate and evaluate unlike black boxes in neural networks Random ForestIn a random forest a machine learning algorithm combines the results of many decision trees to predict a value or class Gratitude for perusing my article till the end I hope you realized something unique today If you enjoyed this article then please share with your buddies and if you have suggestions or thoughts to share with me then please write in the comment box	2022-09-11 15:14:25
海外TECH	DEV Community	Docker Stats | Understand how to monitor Docker Metrics with docker stats	https://dev.to/danielfavour/docker-stats-understand-how-to-monitor-docker-metrics-with-docker-stats-48cl	Docker Stats Understand how to monitor Docker Metrics with docker statsThis article was originally posted on SigNoz and written by me Docker containers are transient lasting for a very short time spawning quickly and in high numbers which causes metrics bursts This makes monitoring a challenge due to Docker s scaling and redeployment features Docker stats is a built in feature of Docker containers The docker stats command returns a live data stream of your running containers Docker is a containerization platform that lets you separate your applications from your infrastructure to deliver software quickly To monitor Docker it is crucial to gather performance related metrics from various system elements such as containers hosts and databases Methods of monitoring Docker MetricsThere are several ways in which Docker metrics can be monitored These include Docker stats commandPseudo files in sysfsREST API exposed by the Docker daemonNote that these are in built features of Docker Observability for your containerized applicationObservability is critical for modern cloud native applications It helps engineering teams have more confidence in their production environment Troubleshooting performance issues is easier with a robust observability framework in place SigNoz an open source observability tool can help make your containerized applications observable In this article we will deep dive into the docker stats command that can be used to monitor Docker metrics right from the terminal What is the docker stats command The docker stats command is a built in feature of Docker that displays resource consumption statistics for the container in real time By default it shows CPU and memory utilization for all containers Stats here refers to “statistics You can restrict the statistics by entering the container names or IDs you re interested in monitoring The docker stats command output includes CPU stats memory metrics block I O and network IO metrics for all active containers A Practical ApproachRunning the docker stats command produces an output that looks like the code snippet below This command shows the stats for all the running Docker containers docker statsCONTAINER ID NAME CPU MEM USAGE LIMIT MEM NET I O BLOCK I O PIDSbfbsd nginx container MiB GiB B B kb B bc ubuntu MiB GiB kb B MB B afcbae hello world MiB GiB kb B kb B Understanding the docker stats command outputThe docker stats command returns a live snapshot of resource usage by Docker containers Let s break down all the stats given by the command CPU statsCPU is expressed as a percentage of the overall host capacity One can optimize the resource usage of Docker hosts by being aware of how much CPU the hosts and containers consume One active busy container shouldn t slow down other containers by consuming all of the CPU resources Containers can be optimized based on the amount of CPU they are using MEM USAGE LIMIT StatsMEM USAGE lists the available memory It gives a quick overview of the container s memory usage and allocation providing information about the container s memory statistics including usage and memory limit Except when it is defined for a specific container the memory usage limit corresponds to the host machine s memory limit MEM StatMEM shows the memory percentage that the container is using from its host machine Network NET I O StatsNET I O shows the volume of information the container s network interface has transmitted TX and received RX It represents network traffic BLOCK I O StatsBLOCK I O helps to identify containers that are writing data and shows the total number of bytes read and written to the container file system Block I O stats can give you an idea about issues with data persistence PIDSPIDS is a count of the processes that the container has created or the number of kernel process IDs running inside the corresponding container More on the usage of docker statsGetting stats of a particular containerTo get the stats of a particular container provide the container Id and run the command docker stats lt containerID gt docker stats bfbsd CONTAINER ID NAME CPU MEM USAGE LIMIT MEM NET I O BLOCK I O PIDSbfbsd nginx container MiB GiB B B kb B You can also get the stats of multiple containers by name and id if you rundocker stats lt containerName gt lt containerId gt docker stats ubuntu bfbsdCONTAINER ID NAME CPU MEM USAGE LIMIT MEM NET I O BLOCK I O PIDSbc ubuntu MiB GiB kb B MB B bfbsd nginx container MiB GiB B B kb B Display options that Docker ProvidesThese display options allow you to specify how you want the output to be shown Docker stats offers the following options for display all which shows all containers whether stopped or running format which uses the Go Template syntax to print images out no stream which disables streaming stats and only pulls the first result no trunc which instructs Docker not to truncate shorten output The syntax for this is shown below docker stats OPTIONS CONTAINER Using docker stats formatLet s take a look at the format option Docker format is used to modify the output format of commands that have the format option If a command supports this option it can be used to change the output format of the command to suit our needs since the default command does not display all the fields connected to that object By using the Go Template syntax the formatting option format presents container output in an easy to read way For example docker stats format Container CPUPerc bc bfbsd This prints out all images with the Container and CPUPerc CPU Percentage elements separated by a colon and it uses a template without headers To display all container information in a table format including name CPU percentage and memory consumption use the following syntax docker stats format table Container t CPUPerc t MemUsage CONTAINER ID CPU PRIV WORKING SETbfbsd MiB GiBbc MiB GiBafcbae MiB GiBHere is the list of applicable placeholders to use with the Go template syntax Placeholder Description container Container name or ID user input Name Container name ID Container ID CPUPerc CPU percentage MemUsage Memory usage NetIO Network IO BlockIO Block IO MemPerc Memory percentage Not available on Windows PIDs Number of PIDs Not available on Windows Final ThoughtsIn this article we discussed ways to monitor resource usage metrics in Docker focused on the docker stats command Other ways of using The Docker stats Pseudo files in sysfs and REST API exposed by the Docker daemon are native ways of monitoring resource utilization metrics Docker container monitoring is critical for running containerized applications For a robust monitoring and observability setup you need to use a tool that visualizes the metrics important for container monitoring and also lets you set alerts on critical metrics SigNoz is an open source observability tool that can help you do that It uses OpenTelemetry to collect metrics from your containers for monitoring OpenTelemetry is becoming the world standard for instrumentation of cloud native applications and it is backed by CNCF foundation the same foundation under which Kubernetes graduated If you want to set up a robust observability framework for your containerized application you can use SigNoz You can create unified views to monitor your Docker containers effectively You can check out the SigNoz GitHub repo here	2022-09-11 15:03:00
海外TECH	Engadget	Disney is remastering Sega Genesis classic ‘Gargoyles’	https://www.engadget.com/disney-remastering-garogyles-155559137.html?src=rss	Disney is remastering Sega Genesis classic Gargoyles Fans of Disney s mid s output got a surprise treat this week During its recent gaming showcase the company revealed it was remastering Gargoyles Alongside Aladdin and The Lion King the Sega Genesis release is one of the highlights of Disney s gaming catalog If you re unfamiliar with the game it s based on the animated series of the same name Gargoyles initially aired between and While it was a modest success then it has since become a cult classic thanks to its compelling story and a stellar voice cast that included Star Trek The Next Generation s Jonathan Frakes and Marina Sirtis Empty Clip Studios best known for its work on Dead Island Retro Revenge is remastering the game for modern consoles and PC The original is known for being one of the best looking games in the Genesis library It also featured a soundtrack by Michael Giacchino who later went on to work on The Incredibles Ratatouille Lost and Rogue One among a lot of other high profile films and TV shows The remaster does not have a release date yet	2022-09-11 15:55:59
ニュース	BBC News - Home	Queen Elizabeth II's cortege arrives to huge crowds in Edinburgh	https://www.bbc.co.uk/news/uk-62867444?at_medium=RSS&at_campaign=KARANGA	balmoral	2022-09-11 15:55:11
ニュース	BBC News - Home	Prince of Wales says new title is an honour	https://www.bbc.co.uk/news/uk-wales-62870604?at_medium=RSS&at_campaign=KARANGA	charles	2022-09-11 15:51:01
ニュース	BBC News - Home	Racing honours Queen at rescheduled St Leger	https://www.bbc.co.uk/sport/horse-racing/62866439?at_medium=RSS&at_campaign=KARANGA	elizabeth	2022-09-11 15:13:16
ニュース	BBC News - Home	Queen's final Scottish journey charts a life of service	https://www.bbc.co.uk/news/uk-scotland-62862379?at_medium=RSS&at_campaign=KARANGA	towns	2022-09-11 15:24:37
ニュース	BBC News - Home	England v South Africa: Ollie Robinson gets the wickets of Wiaan Mulder and Khaya Zondo	https://www.bbc.co.uk/sport/av/cricket/62868943?at_medium=RSS&at_campaign=KARANGA	England v South Africa Ollie Robinson gets the wickets of Wiaan Mulder and Khaya ZondoOllie Robinson gets the wickets of Wiaan Mulder and Khaya Zondo in quick succession to reduce South Africa to on day four of the third Test at The Oval	2022-09-11 15:12:25
ニュース	BBC News - Home	National League games to go ahead from Monday as football restarts in England	https://www.bbc.co.uk/sport/football/62869041?at_medium=RSS&at_campaign=KARANGA	National League games to go ahead from Monday as football restarts in EnglandNational League fixtures will go ahead on Monday after football paused as a mark of respect following the death of Queen Elizabeth II	2022-09-11 15:29:02
北海道	北海道新聞	ＫＤＤＩで通信障害、１０分後に復旧　北海道など１６都道県で	https://www.hokkaido-np.co.jp/article/729519/	kddiau	2022-09-12 00:17:27
北海道	北海道新聞	伊東は後半途中退く　サッカー、フランス１部	https://www.hokkaido-np.co.jp/article/729522/	後半途中	2022-09-12 00:22:00
北海道	北海道新聞	ドウデュースは４着　フランス競馬のニエル賞	https://www.hokkaido-np.co.jp/article/729521/	凱旋門賞	2022-09-12 00:14:00
北海道	北海道新聞	Ｆ１イタリアＧＰ、角田は１４位　フェルスタッペン今季１１勝目	https://www.hokkaido-np.co.jp/article/729520/	角田	2022-09-12 00:14:00